Super‐Resolution MRI–Derived Tumor‐Stroma Ratio Phenotyping for Prognostic and Therapeutic Stratification in Pancreatic Ductal Adenocarcinoma

Abstract

Pancreatic ductal adenocarcinoma (PDAC) exhibits profound stromal heterogeneity that influences tumor progression, recurrence risk, and therapeutic response; however, stromal phenotypes are currently assessed by postoperative histopathology. Here, we developed a super‐resolution MRI (srMRI)–based radiomics model to enable noninvasive tumor‐stroma ratio (TSR) phenotyping in PDAC. Using multicenter cohorts comprising 737 patients, we constructed a srMRI‐derived TSR‐radscore capable of predicting pathological TSR with high accuracy (AUC = 0.870 and 0.791 in training and external validation cohorts). The TSR‐radscore independently stratified recurrence‐free survival and, when integrated with clinicopathological variables, improved early recurrence prediction in an independent surgical cohort. In a locally advanced PDAC cohort, srMRI‐derived TSR was associated with distinct therapeutic outcomes, with H‐TSR tumors showing improved survival under systemic therapy and an association with outcomes following immune checkpoint inhibitor‐based combination therapy. Transcriptomic analyses revealed that L‐TSR tumors were enriched in extracellular matrix remodeling and TGF‐β–related signaling pathways. Single‐cell profiling further uncovered distinct cancer‐associated fibroblast and T‐cell states across TSR phenotypes, linking imaging‐derived TSR patterns to underlying stromal and immune microenvironmental programs. Collectively, srMRI‐derived TSR phenotyping provides a noninvasive and biologically interpretable biomarker for stromal characterization in PDAC, enabling improved recurrence‐risk stratification and pre‐treatment clinical assessment.